knitr::opts_chunk$set(echo = TRUE)
cmdstanr::set_cmdstan_path(path = "C:/Users/kueng/.cmdstan/cmdstan-2.35.0")
library(tidyverse)
library(R.utils)
library(wbCorr)
library(readxl)
library(kableExtra)
library(brms)
library(bayesplot)
library(beepr)
library(DHARMa)
source(file.path('Functions', 'ReportModels.R'))
source(file.path('Functions', 'PrettyTables.R'))
source(file.path('Functions', 'ReportMeasures.R'))
source(file.path('Functions', 'PrepareData.R'))## [1] 1116
# Set options for analysis
use_mi = FALSE
shutdown = FALSE
report_ordinal = FALSE
options(
dplyr.print_max = 100,
brms.backend = 'cmdstan',
brms.file_refit = ifelse(use_mi, 'never', 'on_change'),
brms.file_refit = 'on_change',
#brms.file_refit = 'always',
error = function() beepr::beep(sound = 5),
es.use_symbols = TRUE
)
####################### Model parameters #######################
iterations = 5000 # 10'000 per chain to achieve 40'000
warmup = 2000
# NO AR!!!
#corstr = 'ar'
#corstr = 'cosy_couple'
#corstr = 'cosy_couple:user'
################################################################
suffix = as.character(iterations)df <- openxlsx::read.xlsx(file.path('long.xlsx'))
df_original <- df
df_double <- prepare_data(df, recode_pushing = TRUE, use_mi = use_mi)[[1]]Constructing scales Re-coding pusing reshaping data (4field) centering data within and between
# For indistinguishable Dyads
model_rows_fixed <- c(
'Intercept',
# '-- WITHIN PERSON MAIN EFFECTS --',
'persuasion_self_cw',
'persuasion_partner_cw',
'pressure_self_cw',
'pressure_partner_cw',
'pushing_self_cw',
'pushing_partner_cw',
'day',
'weartime_self_cw',
# '-- BETWEEN PERSON MAIN EFFECTS',
'persuasion_self_cb',
'persuasion_partner_cb',
'pressure_self_cb',
'pressure_partner_cb',
'pushing_self_cb',
'pushing_partner_cb',
'weartime_self_cb'
)
model_rows_fixed_ordinal <- c(
model_rows_fixed[1],
'Intercept[1]',
'Intercept[2]',
'Intercept[3]',
'Intercept[4]',
'Intercept[5]',
model_rows_fixed[2:length(model_rows_fixed)]
)
model_rows_random <- c(
# '--------------',
# '-- RANDOM EFFECTS --',
'sd(Intercept)',
'sd(persuasion_self_cw)',
'sd(persuasion_partner_cw)',
'sd(pressure_self_cw)',
'sd(pressure_partner_cw)',
'sd(pushing_self_cw)',
'sd(pushing_partner_cw)',
# '-- CORRELATION STRUCTURE -- ',
'ar[1]',
'ma[1]',
'cosy',
'nu',
'shape',
'sderr',
'sigma'
)
model_rows_random_ordinal <- c(model_rows_random,'disc')# For indistinguishable Dyads
model_rownames_fixed <- c(
'Intercept',
# '-- WITHIN PERSON MAIN EFFECTS --',
'Daily received persuasion target -> target',
'Daily received persuasion target -> agent',
'Daily received pressure target -> target',
'Daily received pressure target -> agent',
'Daily received pushing target -> target',
'Daily received pushing target -> agent',
'Day',
'Daily weartime',
# '-- BETWEEN PERSON MAIN EFFECTS',
'Mean received persuasion target -> target',
'Mean received persuasion target -> agent',
'Mean received pressure target -> target',
'Mean received pressure target -> agent',
'Mean received pushing target -> target',
'Mean received pushing target -> agent',
'Mean weartime'
)
model_rownames_fixed_ordinal <- c(
model_rownames_fixed[1],
'Intercept[1]',
'Intercept[2]',
'Intercept[3]',
'Intercept[4]',
'Intercept[5]',
model_rownames_fixed[2:length(model_rownames_fixed)]
)
model_rownames_random <- c(
# '--------------',
# '-- RANDOM EFFECTS --',
'sd(Intercept)',
'sd(Daily received persuasion target -> target)',
'sd(Daily received persuasion target -> agent)',
'sd(Daily received pressure target -> target)',
'sd(Daily received pressure target -> agent)',
'sd(Daily received pushing target -> target)',
'sd(Daily received pushing target -> agent)',
# '-- CORRELATION STRUCTURE -- ',
'ar[1]',
'ma[1]',
'cosy',
'nu',
'shape',
'sderr',
'sigma'
)
model_rownames_random_ordinal <- c(model_rownames_random,'disc')# For indistinguishable Dyads
model_rownames_fixed <- c(
"Intercept",
# "-- WITHIN PERSON MAIN EFFECTS --",
"Daily persuasion experienced",
"Daily persuasion utilized (partner's view)", # OR partner received
"Daily pressure experienced",
"Daily pressure utilized (partner's view)",
"Daily pushing experienced",
"Daily pushing utilized (partner's view)",
"Day",
"Daily weartime",
# "-- BETWEEN PERSON MAIN EFFECTS",
"Mean persuasion experienced",
"Mean persuasion utilized (partner's view)",
"Mean pressure experienced",
"Mean pressure utilized (partner's view)",
"Mean pushing experienced",
"Mean pushing utilized (partner's view)",
"Mean weartime"
)
model_rownames_fixed_ordinal <- c(
model_rownames_fixed[1],
'Intercept[1]',
'Intercept[2]',
'Intercept[3]',
'Intercept[4]',
'Intercept[5]',
model_rownames_fixed[2:length(model_rownames_fixed)]
)
model_rownames_random <- c(
# '--------------',
# '-- RANDOM EFFECTS --',
'sd(Intercept)',
"sd(Daily persuasion experienced)",
"sd(Daily persuasion utilized (partner's view))", # OR partner received
"sd(Daily pressure experienced)",
"sd(Daily pressure utilized (partner's view))",
"sd(Daily pushing experienced)",
"sd(Daily pushing utilized (partner's view))",
# '-- CORRELATION STRUCTURE -- ',
'ar[1]',
'ma[1]',
'cosy',
'nu',
'shape',
'sderr',
'sigma'
)
model_rownames_random_ordinal <- c(model_rownames_random,'disc')rows_to_pack <- list(
"Within-Person Effects" = c(2,9),
"Between-Person Effects" = c(10,16),
"Random Effects" = c(17, 23),
"Additional Parameters" = c(24,30)
)
rows_to_pack_ordinal <- list(
"Intercepts" = c(1,6),
"Within-Person Effects" = c(2+5,9+5),
"Between-Person Effects" = c(10+5,16+5),
"Random Effects" = c(17+5, 23+5),
"Additional Parameters" = c(24+5,30+6)
)HURDLE MODELS
# For indistinguishable Dyads
model_rows_fixed_hu <- c(
'Intercept',
'hu_Intercept',
# '-- WITHIN PERSON MAIN EFFECTS --',
'persuasion_self_cw',
'persuasion_partner_cw',
'pressure_self_cw',
'pressure_partner_cw',
'pushing_self_cw',
'pushing_partner_cw',
'day',
'weartime_self_cw',
# '-- BETWEEN PERSON MAIN EFFECTS',
'persuasion_self_cb',
'persuasion_partner_cb',
'pressure_self_cb',
'pressure_partner_cb',
'pushing_self_cb',
'pushing_partner_cb',
'weartime_self_cb',
# HURDLE MODEL
# '-- WITHIN PERSON MAIN EFFECTS --',
'hu_persuasion_self_cw',
'hu_persuasion_partner_cw',
'hu_pressure_self_cw',
'hu_pressure_partner_cw',
'hu_pushing_self_cw',
'hu_pushing_partner_cw',
'hu_day',
'hu_weartime_self_cw',
# '-- BETWEEN PERSON MAIN EFFECTS',
'hu_persuasion_self_cb',
'hu_persuasion_partner_cb',
'hu_pressure_self_cb',
'hu_pressure_partner_cb',
'hu_pushing_self_cb',
'hu_pushing_partner_cb',
'hu_weartime_self_cb'
)
model_rows_random_hu <- c(
# '--------------',
# '-- RANDOM EFFECTS --',
'sd(Intercept)',
'sd(hu_Intercept)',
'sd(persuasion_self_cw)',
'sd(persuasion_partner_cw)',
'sd(pressure_self_cw)',
'sd(pressure_partner_cw)',
'sd(pushing_self_cw)',
'sd(pushing_partner_cw)',
# HURDLE
'sd(hu_persuasion_self_cw)',
'sd(hu_persuasion_partner_cw)',
'sd(hu_pressure_self_cw)',
'sd(hu_pressure_partner_cw)',
'sd(hu_pushing_self_cw)',
'sd(hu_pushing_partner_cw)',
# '-- CORRELATION STRUCTURE -- ',
'ar[1]',
'ma[1]',
'cosy',
'nu',
'shape',
'sderr',
'sigma'
)# For indistinguishable Dyads
model_rownames_fixed_hu <- c(
"Intercept",
"Hurdle Intercept",
# "-- WITHIN PERSON MAIN EFFECTS --",
"Daily persuasion experienced",
"Daily persuasion utilized (partner's view)", # OR partner received
"Daily pressure experienced",
"Daily pressure utilized (partner's view)",
"Daily pushing experienced",
"Daily pushing utilized (partner's view)",
"Day",
"Daily weartime",
# "-- BETWEEN PERSON MAIN EFFECTS",
"Mean persuasion experienced",
"Mean persuasion utilized (partner's view)",
"Mean pressure experienced",
"Mean pressure utilized (partner's view)",
"Mean pushing experienced",
"Mean pushing utilized (partner's view)",
"Mean weartime",
# HURDLE
# "-- WITHIN PERSON MAIN EFFECTS --",
"Hu Daily persuasion experienced",
"Hu Daily persuasion utilized (partner's view)", # OR partner received
"Hu Daily pressure experienced",
"Hu Daily pressure utilized (partner's view)",
"Hu Daily pushing experienced",
"Hu Daily pushing utilized (partner's view)",
"Hu Day",
"Hu Daily weartime",
# "-- BETWEEN PERSON MAIN EFFECTS",
"Hu Mean persuasion experienced",
"Hu Mean persuasion utilized (partner's view)",
"Hu Mean pressure experienced",
"Hu Mean pressure utilized (partner's view)",
"Hu Mean pushing experienced",
"Hu Mean pushing utilized (partner's view)",
"Hu Mean weartime"
)
model_rownames_random_hu <- c(
# '--------------',
# '-- RANDOM EFFECTS --',
'sd(Intercept)',
'sd(Hurdle Intercept)',
"sd(Daily persuasion experienced)",
"sd(Daily persuasion utilized (partner's view))", # OR partner received
"sd(Daily pressure experienced)",
"sd(Daily pressure utilized (partner's view))",
"sd(Daily pushing experienced)",
"sd(Daily pushing utilized (partner's view))",
# Hurdle
"sd(Hu Daily persuasion experienced)",
"sd(Hu Daily persuasion utilized (partner's view))", # OR partner received
"sd(Hu Daily pressure experienced)",
"sd(Hu Daily pressure utilized (partner's view))",
"sd(Hu Daily pushing experienced)",
"sd(Hu Daily pushing utilized (partner's view))",
# '-- CORRELATION STRUCTURE -- ',
'ar[1]',
'ma[1]',
'cosy',
'nu',
'shape',
'sderr',
'sigma'
)rows_to_pack_hu <- list(
"Conditional Within-Person Effects" = c(3,10),
"Conditional Between-Person Effects" = c(11,17),
"Hurdle Within-Person Effects" = c(18,25),
"Hurdle Between-Person Effects" = c(26,32),
"Random Effects" = c(33, 46),
"Additional Parameters" = c(47,53)
)## [1] 0 720
formula <- bf(
pa_sub ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(1 + persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID),
hu = ~ persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(1 + persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 1.5)", class = "b")
, brms::set_prior("normal(0, 2.5", class = "b", dpar = "hu")
, brms::set_prior("normal(0, 50)", class = "Intercept") # for non-zero PA
, brms::set_prior("normal(6, 2.5)", class = "Intercept", dpar = 'hu') # hurdle part
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
#, brms::set_prior("normal(10, 10", class = "shape")
#, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = hurdle_lognormal()
#)
#df_minimal <- df_double[, c("AorB", all.vars(as.formula(formula)))]
pa_sub <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = brms::hurdle_lognormal(),
#family = brms::hurdle_negbinomial(),
#family = brms::hurdle_poisson(),
#control = list(adapt_delta = 0.95, max_treedepth = 15),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("pa_sub_hu_lognormal_NOAR", suffix))
#, file_refit = 'always'
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
## Warning: Found 1 observations with a pareto_k > 0.7 in model 'model'. We
## recommend to set 'moment_match = TRUE' in order to perform moment matching for
## problematic observations.
##
## Computed from 12000 by 3736 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -10490.4 166.5
## p_loo 181.4 6.2
## looic 20980.8 332.9
## ------
## MCSE of elpd_loo is NA.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.6, 1.7]).
##
## Pareto k diagnostic values:
## Count Pct. Min. ESS
## (-Inf, 0.7] (good) 3735 100.0% 605
## (0.7, 1] (bad) 1 0.0% <NA>
## (1, Inf) (very bad) 0 0.0% <NA>
## See help('pareto-k-diagnostic') for details.
##
## DHARMa bootstrapped outlier test
##
## data: model.check
## outliers at both margin(s) = 9, observations = 3736, p-value = 0.34
## alternative hypothesis: two.sided
## percent confidence interval:
## 0.0005353319 0.0032119914
## sample estimates:
## outlier frequency (expected: 0.00164346895074946 )
## 0.002408994
In this instance, the warning about max treedepth is a false positive. We have set treedepth to 15, and when we check with shinystan, we see that treedepth is consistently between 10 and 14.
summarize_brms(
pa_sub,
model_rows_fixed = model_rows_fixed_hu,
model_rows_random = model_rows_random_hu,
model_rownames_fixed = model_rownames_fixed_hu,
model_rownames_random = model_rownames_random_hu,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack_hu
)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
## Warning in summarize_brms(pa_sub, model_rows_fixed = model_rows_fixed_hu, :
## Coefficients were exponentiated. Double check if this was intended.
| exp(Est.) | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 47.90* | 42.22 | 54.30 | 1.001 | 3264.34 | 5142.29 | 1.000 | >100 | Overwhelming Evidence |
| Hurdle Intercept | 1.21 | 0.87 | 1.69 | 1.004 | 2283.61 | 4134.98 | 0.868 | 0.010 | Very Strong Evidence for Null |
| Conditional Within-Person Effects | |||||||||
| Daily persuasion experienced | 1.03 | 0.97 | 1.08 | 1.000 | 4843.30 | 7119.87 | 0.828 | 0.028 | Very Strong Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.03 | 0.98 | 1.08 | 1.000 | 7049.70 | 8420.12 | 0.899 | 0.036 | Strong Evidence for Null |
| Daily pressure experienced | 0.89* | 0.80 | 0.99 | 1.000 | 10401.96 | 7267.03 | 0.984 | 0.485 | Weak Evidence for Null |
| Daily pressure utilized (partner’s view) | 0.94 | 0.86 | 1.03 | 1.000 | 9300.98 | 8275.12 | 0.915 | 0.075 | Strong Evidence for Null |
| Daily pushing experienced | 1.03 | 0.96 | 1.10 | 1.001 | 7999.07 | 8660.16 | 0.775 | 0.032 | Strong Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.99 | 0.93 | 1.05 | 1.001 | 8640.96 | 8974.16 | 0.618 | 0.022 | Very Strong Evidence for Null |
| Day | 1.01 | 0.89 | 1.13 | 1.000 | 15082.98 | 9601.07 | 0.551 | 0.041 | Strong Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.01 | 0.74 | 1.38 | 1.000 | 2732.50 | 4099.77 | 0.533 | 0.102 | Moderate Evidence for Null |
| Mean persuasion utilized (partner’s view) | 0.98 | 0.72 | 1.33 | 1.001 | 2757.84 | 4589.86 | 0.543 | 0.104 | Moderate Evidence for Null |
| Mean pressure experienced | 1.15 | 0.80 | 1.65 | 1.001 | 4069.38 | 5900.07 | 0.772 | 0.162 | Moderate Evidence for Null |
| Mean pressure utilized (partner’s view) | 0.89 | 0.62 | 1.29 | 1.001 | 4198.01 | 6525.04 | 0.744 | 0.150 | Moderate Evidence for Null |
| Mean pushing experienced | 1.32 | 0.84 | 2.07 | 1.000 | 3876.54 | 6233.24 | 0.891 | 0.325 | Weak Evidence for Null |
| Mean pushing utilized (partner’s view) | 1.40 | 0.88 | 2.21 | 1.001 | 3732.45 | 6367.29 | 0.925 | 0.451 | Weak Evidence for Null |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Within-Person Effects | |||||||||
| Hu Daily persuasion experienced | 0.65* | 0.57 | 0.73 | 1.000 | 7700.05 | 7679.91 | 1.000 | >100 | Overwhelming Evidence |
| Hu Daily persuasion utilized (partner’s view) | 0.75* | 0.67 | 0.84 | 1.001 | 9038.94 | 9018.25 | 1.000 | >100 | Overwhelming Evidence |
| Hu Daily pressure experienced | 1.23 | 0.88 | 1.71 | 1.000 | 8879.51 | 8110.20 | 0.898 | 0.154 | Moderate Evidence for Null |
| Hu Daily pressure utilized (partner’s view) | 0.66* | 0.42 | 0.95 | 1.000 | 8465.74 | 6511.93 | 0.988 | 0.899 | Weak Evidence for Null |
| Hu Daily pushing experienced | 0.58* | 0.40 | 0.78 | 1.000 | 7544.89 | 7513.38 | 1.000 | 24.845 | Strong Evidence |
| Hu Daily pushing utilized (partner’s view) | 0.54* | 0.41 | 0.69 | 1.000 | 7450.70 | 6837.16 | 1.000 | >100 | Overwhelming Evidence |
| Hu Day | 1.09 | 0.85 | 1.42 | 1.000 | 15446.28 | 9424.26 | 0.750 | 0.065 | Strong Evidence for Null |
| Hu Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Between-Person Effects | |||||||||
| Hu Mean persuasion experienced | 0.83 | 0.36 | 1.87 | 1.001 | 1923.05 | 3521.20 | 0.680 | 0.184 | Moderate Evidence for Null |
| Hu Mean persuasion utilized (partner’s view) | 0.83 | 0.36 | 1.89 | 1.001 | 1908.01 | 3480.06 | 0.671 | 0.183 | Moderate Evidence for Null |
| Hu Mean pressure experienced | 3.31* | 1.36 | 8.35 | 1.000 | 2952.14 | 5126.23 | 0.995 | 6.166 | Moderate Evidence |
| Hu Mean pressure utilized (partner’s view) | 1.79 | 0.74 | 4.48 | 1.000 | 3052.79 | 5306.39 | 0.905 | 0.427 | Weak Evidence for Null |
| Hu Mean pushing experienced | 0.35 | 0.11 | 1.11 | 1.002 | 2801.73 | 4512.72 | 0.962 | 1.144 | Weak Evidence |
| Hu Mean pushing utilized (partner’s view) | 0.34 | 0.11 | 1.10 | 1.002 | 2692.83 | 4957.40 | 0.964 | 1.280 | Weak Evidence |
| Hu Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 0.32 | 0.24 | 0.42 | 1.00 | 3342.49 | 5207.28 | NA | NA | NA |
| sd(Hurdle Intercept) | 0.90 | 0.69 | 1.17 | 1.00 | 3026.08 | 5383.96 | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.12 | 0.08 | 0.17 | 1.00 | 5467.59 | 7369.26 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.09 | 0.05 | 0.13 | 1.00 | 6402.38 | 7446.13 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.08 | 0.00 | 0.24 | 1.00 | 4554.51 | 5172.98 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.07 | 0.00 | 0.19 | 1.00 | 5546.07 | 5814.39 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.11 | 0.04 | 0.19 | 1.00 | 5412.48 | 4100.25 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.09 | 0.02 | 0.17 | 1.00 | 3656.04 | 2742.82 | NA | NA | NA |
| sd(Hu Daily persuasion experienced) | 0.18 | 0.02 | 0.34 | 1.00 | 3562.02 | 3269.27 | NA | NA | NA |
| sd(Hu Daily persuasion utilized (partner’s view)) | 0.17 | 0.03 | 0.33 | 1.00 | 4124.75 | 3957.26 | NA | NA | NA |
| sd(Hu Daily pressure experienced) | 0.31 | 0.01 | 0.89 | 1.00 | 3857.92 | 3643.66 | NA | NA | NA |
| sd(Hu Daily pressure utilized (partner’s view)) | 0.34 | 0.01 | 0.99 | 1.00 | 4446.62 | 5916.04 | NA | NA | NA |
| sd(Hu Daily pushing experienced) | 0.64 | 0.32 | 1.07 | 1.00 | 5132.64 | 7726.03 | NA | NA | NA |
| sd(Hu Daily pushing utilized (partner’s view)) | 0.32 | 0.05 | 0.64 | 1.00 | 4284.77 | 4067.55 | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | 0.68 | 0.66 | 0.71 | 1.00 | 15422.04 | 8395.04 | NA | NA | NA |
mcmc_plot(pa_sub,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)mcmc_plot(pa_sub,
variable = c(
'b_hu_persuasion_self_cw',
'b_hu_persuasion_partner_cw',
'b_hu_pressure_self_cw',
'b_hu_pressure_partner_cw',
'b_hu_pushing_self_cw',
'b_hu_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95
)plot(
bayestestR::p_direction(pa_sub),
priors = TRUE
) +
#coord_cartesian(xlim = c(-3, 3)) +
theme_bw()## Warning in get_priors.brmsfit(model, effects = effects, component = component,
## : NAs introduced by coercion
## Warning in get_priors.brmsfit(model, effects = effects, component = component,
## : NAs introduced by coercion
## Warning: `b_hu_persuasion_self_cw`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_persuasion_partner_cw`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pressure_self_cw`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pressure_partner_cw`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pushing_self_cw`, or one of its groups specified in `by`, is empty
## and has no density information.
## Warning: `b_hu_pushing_partner_cw`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_persuasion_self_cb`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_persuasion_partner_cb`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pressure_self_cb`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pressure_partner_cb`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_pushing_self_cb`, or one of its groups specified in `by`, is empty
## and has no density information.
## Warning: `b_hu_pushing_partner_cb`, or one of its groups specified in `by`, is
## empty and has no density information.
## Warning: `b_hu_day`, or one of its groups specified in `by`, is empty and has no
## density information.
## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
conditional_spaghetti(
pa_sub,
effects = c('persuasion_self_cw',
'persuasion_partner_cw',
'pressure_self_cw',
'pressure_partner_cw',
'pushing_self_cw',
'pushing_partner_cw'),
group_var = 'coupleID',
plot_full_range = TRUE
)## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
\(persuasion_self_cw_count
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-4.png"
width="2400" />\)persuasion_self_cw_hurdle
\(persuasion_self_cw_combined
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-6.png"
width="2400" />\)persuasion_partner_cw_count
\(persuasion_partner_cw_hurdle
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-8.png"
width="2400" />\)persuasion_partner_cw_combined
\(pressure_self_cw_count
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-10.png"
width="2400" />\)pressure_self_cw_hurdle
\(pressure_self_cw_combined
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-12.png"
width="2400" />\)pressure_partner_cw_count
\(pressure_partner_cw_hurdle
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-14.png"
width="2400" />\)pressure_partner_cw_combined
\(pushing_self_cw_count
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-16.png"
width="2400" />\)pushing_self_cw_hurdle
\(pushing_self_cw_combined
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-18.png"
width="2400" />\)pushing_partner_cw_count
\(pushing_partner_cw_hurdle
<img
src="01_FinalModels_files/figure-html/report_pa_sub_lognormal-20.png"
width="2400" />\)pushing_partner_cw_combined
##
## Estimate 2.5 % 97.5 %
## 30.9 29.4 32.5
##
## Type: response
## Columns: estimate, conf.low, conf.high
Additionally, as a sensitivity analysis, we estimate the two part of the models separately.
The zero vs. 1 modelling part also has high pareto-k values, but reaches the same conslucsions as the hurdle model. We tried further simplifying by removing the residual AR1 correlation structure, which led to a model with good pareto-k values, still arriving at the same conslusion as the original hurdle model:
df_double$pa_sub_zero <- as.factor(ifelse(df_double$pa_sub > 0, 1, 0))
formula <- bf(
pa_sub_zero ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(1 + persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
set_prior("normal(0, 1.5)", class = "b")
, brms::set_prior("normal(0, 5)", class = "Intercept") # for non-zero PA
, brms::set_prior("normal(0, 1)", class = "sd", group = "coupleID")
#, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 1.5)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = bernoulli()
# )
pa_sub_zero_model <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
#family = brms::hurdle_lognormal(),
#family = brms::hurdle_negbinomial(),
family = brms::bernoulli(),
#control = list(adapt_delta = 0.95),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("pa_sub_hu_zero_part_NOAR", suffix))
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
## Warning: Found 2 observations with a pareto_k > 0.7 in model 'model'. We
## recommend to set 'moment_match = TRUE' in order to perform moment matching for
## problematic observations.
##
## Computed from 12000 by 3736 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -2149.7 27.8
## p_loo 93.4 4.1
## looic 4299.5 55.6
## ------
## MCSE of elpd_loo is NA.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.5, 2.3]).
##
## Pareto k diagnostic values:
## Count Pct. Min. ESS
## (-Inf, 0.7] (good) 3734 99.9% 355
## (0.7, 1] (bad) 2 0.1% <NA>
## (1, Inf) (very bad) 0 0.0% <NA>
## See help('pareto-k-diagnostic') for details.
##
## DHARMa bootstrapped outlier test
##
## data: model.check
## outliers at both margin(s) = 0, observations = 3736, p-value = 1
## alternative hypothesis: two.sided
## percent confidence interval:
## 0 0
## sample estimates:
## outlier frequency (expected: 0 )
## 0
summarize_brms(
pa_sub_zero_model,
model_rows_fixed = model_rows_fixed_hu,
model_rows_random = model_rows_random_hu,
model_rownames_fixed = model_rownames_fixed_hu,
model_rownames_random = model_rownames_random_hu,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack_hu
)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
| OR | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 0.84 | 0.61 | 1.15 | 1.001 | 1841.97 | 3973.90 | 0.863 | 0.059 | Strong Evidence for Null |
| Hurdle Intercept | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Within-Person Effects | |||||||||
| Daily persuasion experienced | 1.53* | 1.36 | 1.75 | 1.001 | 8062.00 | 8582.55 | 1.000 | >100 | Overwhelming Evidence |
| Daily persuasion utilized (partner’s view) | 1.33* | 1.19 | 1.50 | 1.000 | 9007.75 | 8833.49 | 1.000 | >100 | Overwhelming Evidence |
| Daily pressure experienced | 0.82 | 0.59 | 1.11 | 1.000 | 10666.20 | 8323.82 | 0.906 | 0.242 | Moderate Evidence for Null |
| Daily pressure utilized (partner’s view) | 1.48* | 1.05 | 2.25 | 1.000 | 10016.51 | 6740.30 | 0.987 | 1.589 | Weak Evidence |
| Daily pushing experienced | 1.72* | 1.28 | 2.43 | 1.000 | 7256.09 | 7373.66 | 1.000 | 37.284 | Very Strong Evidence |
| Daily pushing utilized (partner’s view) | 1.83* | 1.46 | 2.40 | 1.001 | 8929.39 | 8028.12 | 1.000 | >100 | Overwhelming Evidence |
| Day | 0.92 | 0.71 | 1.19 | 1.000 | 18939.10 | 8954.86 | 0.739 | 0.102 | Moderate Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.17 | 0.56 | 2.48 | 1.002 | 1891.71 | 4153.21 | 0.667 | 0.270 | Moderate Evidence for Null |
| Mean persuasion utilized (partner’s view) | 1.17 | 0.57 | 2.44 | 1.002 | 1970.51 | 4133.98 | 0.666 | 0.269 | Moderate Evidence for Null |
| Mean pressure experienced | 0.33* | 0.15 | 0.75 | 1.001 | 2989.43 | 5922.42 | 0.996 | 9.942 | Moderate Evidence |
| Mean pressure utilized (partner’s view) | 0.59 | 0.26 | 1.34 | 1.002 | 3409.72 | 5951.96 | 0.900 | 0.616 | Weak Evidence for Null |
| Mean pushing experienced | 2.45 | 0.84 | 7.10 | 1.001 | 3185.19 | 5355.11 | 0.953 | 1.480 | Weak Evidence |
| Mean pushing utilized (partner’s view) | 2.56 | 0.88 | 7.30 | 1.001 | 3160.95 | 5396.08 | 0.958 | 1.614 | Weak Evidence |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Within-Person Effects | |||||||||
| Hu Daily persuasion experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily persuasion utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Day | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Between-Person Effects | |||||||||
| Hu Mean persuasion experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean persuasion utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 0.89 | 0.68 | 1.14 | 1.00 | 3199.26 | 5243.78 | NA | NA | NA |
| sd(Hurdle Intercept) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.18 | 0.02 | 0.34 | 1.00 | 3164.76 | 2298.66 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.17 | 0.02 | 0.33 | 1.00 | 3506.22 | 3289.23 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.28 | 0.01 | 0.78 | 1.00 | 4188.59 | 5081.55 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.31 | 0.01 | 0.90 | 1.00 | 3962.03 | 5276.36 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.62 | 0.32 | 1.01 | 1.00 | 5746.41 | 6689.15 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.31 | 0.05 | 0.63 | 1.00 | 4373.04 | 3371.61 | NA | NA | NA |
| sd(Hu Daily persuasion experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily persuasion utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | NA | NA | NA | NA | NA | NA | NA | NA | NA |
brms::mcmc_plot(pa_sub_zero_model,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(pa_sub_zero_model),
priors = TRUE
) +
coord_cartesian(xlim = c(-3, 3)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
## Possible multicollinearity between b_persuasion_partner_cb and
## b_persuasion_self_cb (r = 0.81). This might lead to inappropriate
## results. See 'Details' in '?rope'.
conditional_spaghetti(
pa_sub_zero_model,
effects = c('persuasion_self_cw',
'persuasion_partner_cw',
'pressure_partner_cw',
'pushing_self_cw',
'pushing_partner_cw'),
group_var = 'coupleID',
plot_full_range = TRUE
)\(persuasion_self_cw
<img
src="01_FinalModels_files/figure-html/report_pa_sub_separate_inactive-4.png"
width="2400" />\)persuasion_partner_cw
\(pressure_partner_cw
<img
src="01_FinalModels_files/figure-html/report_pa_sub_separate_inactive-6.png"
width="2400" />\)pushing_self_cw
$pushing_partner_cw
##
## Estimate 2.5 % 97.5 %
## 0.447 0.434 0.461
##
## Type: response
## Columns: estimate, conf.low, conf.high
# Only include active days
df_double$pa_sub_non_zero <- ifelse(df_double$pa_sub > 0, df_double$pa_sub, NA)
formula <- bf(
log(pa_sub_non_zero) ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(1 + persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
##, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 2.5)", class = "b")
, brms::set_prior("normal(0, 50)", class = "Intercept") # for non-zero PA
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = gaussian()
# )
pa_sub_active_model <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = gaussian(),
#control = list(adapt_delta = 0.95),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("pa_sub_hu_active_part_NOAR", suffix))
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
##
## Computed from 12000 by 1672 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -1785.5 35.3
## p_loo 85.9 4.1
## looic 3571.1 70.6
## ------
## MCSE of elpd_loo is 0.1.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.5, 2.0]).
##
## All Pareto k estimates are good (k < 0.7).
## See help('pareto-k-diagnostic') for details.
## DHARMa:testOutliers with type = binomial may have inflated Type I error rates for integer-valued distributions. To get a more exact result, it is recommended to re-run testOutliers with type = 'bootstrap'. See ?testOutliers for details
##
## DHARMa bootstrapped outlier test
##
## data: model.check
## outliers at both margin(s) = 8, observations = 1672, p-value = 0.26
## alternative hypothesis: two.sided
## percent confidence interval:
## 0.0005980861 0.0068929426
## sample estimates:
## outlier frequency (expected: 0.00319377990430622 )
## 0.004784689
summarize_brms(
pa_sub_active_model,
model_rows_fixed = model_rows_fixed_hu,
model_rows_random = model_rows_random_hu,
model_rownames_fixed = model_rownames_fixed_hu,
model_rownames_random = model_rownames_random_hu,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack_hu
)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
## Warning in summarize_brms(pa_sub_active_model, model_rows_fixed =
## model_rows_fixed_hu, : Coefficients were exponentiated. Double check if this
## was intended.
| exp(Est.) | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 47.85* | 42.22 | 54.17 | 1.001 | 4041.60 | 6381.47 | 1.000 | >100 | Overwhelming Evidence |
| Hurdle Intercept | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Within-Person Effects | |||||||||
| Daily persuasion experienced | 1.03 | 0.97 | 1.08 | 1.000 | 6597.52 | 8346.37 | 0.833 | 0.018 | Very Strong Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.03 | 0.99 | 1.08 | 1.000 | 8955.61 | 9602.22 | 0.904 | 0.019 | Very Strong Evidence for Null |
| Daily pressure experienced | 0.89* | 0.80 | 0.99 | 1.000 | 14496.32 | 8806.27 | 0.987 | 0.287 | Moderate Evidence for Null |
| Daily pressure utilized (partner’s view) | 0.94 | 0.85 | 1.03 | 1.000 | 13817.24 | 8187.83 | 0.908 | 0.044 | Strong Evidence for Null |
| Daily pushing experienced | 1.03 | 0.96 | 1.10 | 1.000 | 11709.14 | 9409.07 | 0.775 | 0.018 | Very Strong Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.99 | 0.93 | 1.05 | 1.000 | 11995.74 | 10105.19 | 0.633 | 0.014 | Very Strong Evidence for Null |
| Day | 1.01 | 0.89 | 1.14 | 1.000 | 20035.93 | 9281.40 | 0.545 | 0.025 | Very Strong Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.00 | 0.73 | 1.37 | 1.001 | 3231.81 | 4989.35 | 0.510 | 0.063 | Strong Evidence for Null |
| Mean persuasion utilized (partner’s view) | 0.98 | 0.72 | 1.33 | 1.001 | 3286.72 | 5489.83 | 0.560 | 0.061 | Strong Evidence for Null |
| Mean pressure experienced | 1.15 | 0.80 | 1.64 | 1.000 | 5002.27 | 7220.72 | 0.778 | 0.097 | Strong Evidence for Null |
| Mean pressure utilized (partner’s view) | 0.89 | 0.61 | 1.28 | 1.000 | 5018.40 | 7058.04 | 0.732 | 0.088 | Strong Evidence for Null |
| Mean pushing experienced | 1.34 | 0.84 | 2.11 | 1.000 | 4624.61 | 7355.15 | 0.896 | 0.206 | Moderate Evidence for Null |
| Mean pushing utilized (partner’s view) | 1.42 | 0.89 | 2.26 | 1.000 | 4706.03 | 7431.81 | 0.929 | 0.289 | Moderate Evidence for Null |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Within-Person Effects | |||||||||
| Hu Daily persuasion experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily persuasion utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Day | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Between-Person Effects | |||||||||
| Hu Mean persuasion experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean persuasion utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing experienced | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing utilized (partner’s view) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 0.32 | 0.25 | 0.42 | 1.00 | 3621.92 | 6455.57 | NA | NA | NA |
| sd(Hurdle Intercept) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.12 | 0.08 | 0.17 | 1.00 | 7194.08 | 9303.03 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.09 | 0.05 | 0.13 | 1.00 | 8556.16 | 8646.99 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.08 | 0.00 | 0.23 | 1.00 | 5748.83 | 6157.17 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.07 | 0.00 | 0.19 | 1.00 | 6534.51 | 6674.27 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.11 | 0.04 | 0.19 | 1.00 | 5752.73 | 4564.11 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.09 | 0.02 | 0.17 | 1.00 | 5084.36 | 3390.77 | NA | NA | NA |
| sd(Hu Daily persuasion experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily persuasion utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing experienced) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing utilized (partner’s view)) | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | 0.68 | 0.66 | 0.71 | 1.00 | 19220.03 | 8549.91 | NA | NA | NA |
mcmc_plot(pa_sub_active_model,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(pa_sub_active_model),
priors = TRUE
) +
coord_cartesian(xlim = c(-3, 3)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
## Possible multicollinearity between b_persuasion_partner_cb and
## b_persuasion_self_cb (r = 0.77). This might lead to inappropriate
## results. See 'Details' in '?rope'.
conditional_spaghetti(
pa_sub_active_model,
effects = c('pressure_self_cw'),
transform_fn = function(x) {exp(x)},
group_var = 'coupleID',
plot_full_range = TRUE
)$pressure_self_cw
##
## Estimate 2.5 % 97.5 %
## 3.92 3.89 3.95
##
## Type: response
## Columns: estimate, conf.low, conf.high
## [1] 5.75 971.25
formula <- bf(
log(pa_obj) ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day + weartime_self_cw + weartime_self_cb +
# Random effects
(persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 2.5)", class = "b")
, brms::set_prior("normal(0, 50)", class = "Intercept") # for non-zero PA
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = gaussian()
# )
#df_minimal <- df_double[, c("AorB", all.vars(as.formula(formula)))]
pa_obj_log <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = gaussian(),
#control = list(adapt_delta = 0.95),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("pa_obj_log_gaussian_NOAR", suffix))
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
##
## Computed from 12000 by 3337 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -2936.5 56.3
## p_loo 92.1 4.5
## looic 5872.9 112.6
## ------
## MCSE of elpd_loo is 0.1.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.4, 2.3]).
##
## All Pareto k estimates are good (k < 0.7).
## See help('pareto-k-diagnostic') for details.
## DHARMa:testOutliers with type = binomial may have inflated Type I error rates for integer-valued distributions. To get a more exact result, it is recommended to re-run testOutliers with type = 'bootstrap'. See ?testOutliers for details
##
## DHARMa bootstrapped outlier test
##
## data: model.check
## outliers at both margin(s) = 26, observations = 3337, p-value < 2.2e-16
## alternative hypothesis: two.sided
## percent confidence interval:
## 0.001341025 0.005251723
## sample estimates:
## outlier frequency (expected: 0.00302966736589751 )
## 0.007791429
summarize_brms(
pa_obj_log,
model_rows_fixed = model_rows_fixed,
model_rows_random = model_rows_random,
model_rownames_fixed = model_rownames_fixed,
model_rownames_random = model_rownames_random,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
## Warning in summarize_brms(pa_obj_log, model_rows_fixed = model_rows_fixed, :
## Coefficients were exponentiated. Double check if this was intended.
| exp(Est.) | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 117.41* | 105.48 | 130.41 | 1.002 | 1936.20 | 4337.49 | 1.000 | >100 | Overwhelming Evidence |
| Within-Person Effects | |||||||||
| Daily persuasion experienced | 1.03 | 1.00 | 1.06 | 1.000 | 8443.32 | 9440.38 | 0.966 | 0.034 | Strong Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.02 | 0.99 | 1.05 | 1.001 | 10110.26 | 9523.00 | 0.888 | 0.014 | Very Strong Evidence for Null |
| Daily pressure experienced | 0.94 | 0.88 | 1.01 | 1.000 | 13123.29 | 8882.26 | 0.960 | 0.073 | Strong Evidence for Null |
| Daily pressure utilized (partner’s view) | 0.98 | 0.92 | 1.05 | 1.000 | 14150.05 | 9457.65 | 0.714 | 0.015 | Very Strong Evidence for Null |
| Daily pushing experienced | 1.03 | 0.98 | 1.08 | 1.000 | 11136.01 | 8673.71 | 0.900 | 0.024 | Very Strong Evidence for Null |
| Daily pushing utilized (partner’s view) | 1.02 | 0.97 | 1.06 | 1.000 | 15288.78 | 9998.46 | 0.771 | 0.011 | Very Strong Evidence for Null |
| Day | 0.97 | 0.91 | 1.04 | 1.000 | 20771.69 | 8890.89 | 0.785 | 0.019 | Very Strong Evidence for Null |
| Daily weartime | 1.00* | 1.00 | 1.00 | 1.000 | 12258.92 | 8147.17 | 1.000 | 0.067 | Strong Evidence for Null |
| Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.10 | 0.82 | 1.46 | 1.003 | 1635.21 | 3066.39 | 0.748 | 0.074 | Strong Evidence for Null |
| Mean persuasion utilized (partner’s view) | 0.98 | 0.73 | 1.30 | 1.003 | 1664.34 | 3415.83 | 0.559 | 0.059 | Strong Evidence for Null |
| Mean pressure experienced | 0.98 | 0.73 | 1.31 | 1.003 | 2233.86 | 4590.15 | 0.560 | 0.060 | Strong Evidence for Null |
| Mean pressure utilized (partner’s view) | 0.97 | 0.73 | 1.28 | 1.002 | 2141.33 | 4170.53 | 0.594 | 0.060 | Strong Evidence for Null |
| Mean pushing experienced | 0.97 | 0.65 | 1.45 | 1.002 | 2615.53 | 4583.92 | 0.553 | 0.083 | Strong Evidence for Null |
| Mean pushing utilized (partner’s view) | 1.25 | 0.83 | 1.85 | 1.002 | 2546.44 | 4664.09 | 0.859 | 0.146 | Moderate Evidence for Null |
| Mean weartime | 1.00 | 1.00 | 1.00 | 1.000 | 16930.39 | 10509.93 | 0.909 | 0.000 | Very Strong Evidence for Null |
| Random Effects | |||||||||
| sd(Intercept) | 0.31 | 0.24 | 0.40 | 1.00 | 2373.00 | 4540.45 | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.05 | 0.02 | 0.08 | 1.00 | 6108.14 | 4438.88 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.06 | 0.03 | 0.09 | 1.00 | 6116.29 | 5901.98 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.05 | 0.00 | 0.14 | 1.00 | 5104.76 | 5590.89 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.04 | 0.00 | 0.12 | 1.00 | 6898.74 | 5731.73 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.07 | 0.01 | 0.15 | 1.00 | 2745.29 | 3354.31 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.04 | 0.00 | 0.10 | 1.00 | 4176.37 | 5266.68 | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | 0.57 | 0.56 | 0.59 | 1.00 | 19512.21 | 8255.47 | NA | NA | NA |
mcmc_plot(pa_obj_log,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(pa_obj_log),
priors = TRUE
) +
coord_cartesian(xlim = c(-3, 3)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
## Possible multicollinearity between b_persuasion_partner_cb and
## b_persuasion_self_cb (r = 0.89), b_pressure_self_cb and
## b_persuasion_self_cb (r = 0.74), b_pressure_partner_cb and
## b_persuasion_self_cb (r = 0.74), b_pressure_self_cb and
## b_persuasion_partner_cb (r = 0.72), b_pressure_partner_cb and
## b_persuasion_partner_cb (r = 0.78), b_pushing_partner_cb and
## b_pushing_self_cb (r = 0.82). This might lead to inappropriate results.
## See 'Details' in '?rope'.
## [1] 0 5
formula <- bf(
aff ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 5)", class = "b")
,brms::set_prior("normal(0, 20)", class = "Intercept", lb=1, ub=6) # range of the outcome scale
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = gaussian()
# )
#df_minimal <- df_double[, c("AorB", all.vars(as.formula(formula)))]
mood_gauss <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = gaussian(),
#control = list(adapt_delta = 0.95, max_treedepth = 15),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("mood_gauss_NOAR", suffix))
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
##
## Computed from 12000 by 3736 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -5185.9 59.2
## p_loo 75.2 3.3
## looic 10371.7 118.5
## ------
## MCSE of elpd_loo is 0.1.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.5, 2.1]).
##
## All Pareto k estimates are good (k < 0.7).
## See help('pareto-k-diagnostic') for details.
##
## DHARMa outlier test based on exact binomial test with approximate
## expectations
##
## data: model.check
## outliers at both margin(s) = 31, observations = 3736, p-value =
## 9.752e-11
## alternative hypothesis: true probability of success is not equal to 0.001998002
## 95 percent confidence interval:
## 0.00564461 0.01175733
## sample estimates:
## frequency of outliers (expected: 0.001998001998002 )
## 0.008297645
summarize_brms(
mood_gauss,
model_rows_fixed = model_rows_fixed,
model_rows_random = model_rows_random,
model_rownames_fixed = model_rownames_fixed,
model_rownames_random = model_rownames_random,
exponentiate = F) %>%
print_df(rows_to_pack = rows_to_pack)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
| b | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 3.70* | 3.48 | 3.91 | 1.007 | 1299.69 | 2626.71 | 1.000 | >100 | Overwhelming Evidence |
| Within-Person Effects | |||||||||
| Daily persuasion experienced | 0.00 | -0.04 | 0.05 | 1.000 | 10096.58 | 8360.31 | 0.553 | 0.004 | Very Strong Evidence for Null |
| Daily persuasion utilized (partner’s view) | 0.02 | -0.02 | 0.07 | 1.001 | 8776.31 | 8901.48 | 0.829 | 0.007 | Very Strong Evidence for Null |
| Daily pressure experienced | -0.04 | -0.14 | 0.07 | 1.000 | 11418.22 | 8197.57 | 0.767 | 0.013 | Very Strong Evidence for Null |
| Daily pressure utilized (partner’s view) | -0.02 | -0.14 | 0.08 | 1.000 | 10703.53 | 8437.61 | 0.661 | 0.012 | Very Strong Evidence for Null |
| Daily pushing experienced | 0.02 | -0.04 | 0.09 | 1.000 | 11578.47 | 8985.61 | 0.768 | 0.008 | Very Strong Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.08* | 0.01 | 0.14 | 1.000 | 10076.04 | 8287.53 | 0.984 | 0.078 | Strong Evidence for Null |
| Day | 0.26* | 0.15 | 0.37 | 1.001 | 17305.49 | 8858.10 | 1.000 | 50.970 | Very Strong Evidence |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Between-Person Effects | |||||||||
| Mean persuasion experienced | 0.33 | -0.21 | 0.90 | 1.003 | 1324.40 | 2167.41 | 0.889 | 0.117 | Moderate Evidence for Null |
| Mean persuasion utilized (partner’s view) | 0.22 | -0.32 | 0.79 | 1.003 | 1322.88 | 2252.89 | 0.790 | 0.079 | Strong Evidence for Null |
| Mean pressure experienced | -0.31 | -0.86 | 0.23 | 1.003 | 1481.77 | 2769.72 | 0.874 | 0.102 | Moderate Evidence for Null |
| Mean pressure utilized (partner’s view) | -0.30 | -0.84 | 0.24 | 1.003 | 1476.58 | 2758.08 | 0.871 | 0.098 | Strong Evidence for Null |
| Mean pushing experienced | 0.22 | -0.54 | 0.99 | 1.002 | 1997.17 | 3840.31 | 0.714 | 0.096 | Strong Evidence for Null |
| Mean pushing utilized (partner’s view) | 0.35 | -0.39 | 1.12 | 1.002 | 2005.43 | 3822.38 | 0.825 | 0.119 | Moderate Evidence for Null |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 0.60 | 0.47 | 0.78 | 1.00 | 2148.52 | 4074.04 | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.04 | 0.00 | 0.10 | 1.00 | 3348.96 | 5109.75 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.08 | 0.01 | 0.13 | 1.00 | 3084.49 | 2127.56 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.08 | 0.00 | 0.24 | 1.00 | 4964.63 | 5526.49 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.09 | 0.00 | 0.26 | 1.00 | 4911.35 | 5368.11 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.06 | 0.00 | 0.14 | 1.00 | 3656.74 | 3408.48 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.07 | 0.00 | 0.17 | 1.00 | 4184.55 | 4073.31 | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | 0.96 | 0.94 | 0.98 | 1.00 | 18080.51 | 9327.96 | NA | NA | NA |
mcmc_plot(mood_gauss,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(mood_gauss),
priors = TRUE
) +
coord_cartesian(xlim = c(-3, 3)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
## Possible multicollinearity between b_pressure_self_cb and
## b_persuasion_self_cb (r = 0.82), b_pressure_partner_cb and
## b_persuasion_self_cb (r = 0.8), b_pressure_self_cb and
## b_persuasion_partner_cb (r = 0.8), b_pressure_partner_cb and
## b_persuasion_partner_cb (r = 0.82), b_pressure_partner_cb and
## b_pressure_self_cb (r = 0.76), b_pushing_partner_cb and
## b_pushing_self_cb (r = 0.89). This might lead to inappropriate results.
## See 'Details' in '?rope'.
conditional_spaghetti(
mood_gauss,
effects = c('pushing_partner_cw'),
group_var = 'coupleID',
plot_full_range = TRUE
)$pushing_partner_cw
##
## Estimate 2.5 % 97.5 %
## 3.82 3.79 3.85
##
## Type: response
## Columns: estimate, conf.low, conf.high
## [1] 0 5
df_double$reactance_ordinal <- factor(df_double$reactance,
levels = 0:5,
ordered = TRUE)
formula <- bf(
reactance_ordinal ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 2.5)", class = "b")
#, brms::set_prior("normal(0, 10)", class = "Intercept", lb=0, ub=5) # range of the outcome scale
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = cumulative() # HURDLE_CUMULATIVE
# )
#df_minimal <- df_double[, c("AorB", all.vars(as.formula(formula)))]
reactance_ordinal <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = brms::cumulative(),
#control = list(adapt_delta = 0.95),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777
, file = file.path("models_cache_brms", paste0("reactance_ordinal_NOARNOAR_", suffix))
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
## Warning: Found 6 observations with a pareto_k > 0.7 in model 'model'. We
## recommend to set 'moment_match = TRUE' in order to perform moment matching for
## problematic observations.
##
## Computed from 12000 by 756 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -681.9 31.9
## p_loo 73.4 5.4
## looic 1363.8 63.8
## ------
## MCSE of elpd_loo is NA.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.4, 1.7]).
##
## Pareto k diagnostic values:
## Count Pct. Min. ESS
## (-Inf, 0.7] (good) 750 99.2% 445
## (0.7, 1] (bad) 6 0.8% <NA>
## (1, Inf) (very bad) 0 0.0% <NA>
## See help('pareto-k-diagnostic') for details.
##
## DHARMa bootstrapped outlier test
##
## data: model.check
## outliers at both margin(s) = 2, observations = 756, p-value = 0.02
## alternative hypothesis: two.sided
## percent confidence interval:
## 0.000000000 0.001322751
## sample estimates:
## outlier frequency (expected: 0.000291005291005291 )
## 0.002645503
summarize_brms(
reactance_ordinal,
model_rows_fixed = model_rows_fixed_ordinal,
model_rows_random = model_rows_random_ordinal,
model_rownames_fixed = model_rownames_fixed_ordinal,
model_rownames_random = model_rownames_random_ordinal,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack_ordinal)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
| OR | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercepts | |||||||||
| Intercept | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Intercept[1] | 3.85* | 2.33 | 6.45 | 1.000 | 8597.51 | 9211.52 | 1.000 | >100 | Overwhelming Evidence |
| Intercept[2] | 8.35* | 4.95 | 14.45 | 1.000 | 8834.13 | 8761.87 | 1.000 | >100 | Overwhelming Evidence |
| Intercept[3] | 23.24* | 13.13 | 42.31 | 1.000 | 9373.11 | 9135.25 | 1.000 | >100 | Overwhelming Evidence |
| Intercept[4] | 101.58* | 52.10 | 209.10 | 1.000 | 10595.59 | 9691.96 | 1.000 | >100 | Overwhelming Evidence |
| Intercept[5] | 3488.39* | 1077.21 | 13336.21 | 1.001 | 13289.90 | 8614.35 | 1.000 | >100 | Overwhelming Evidence |
| Within-Person Effects | |||||||||
| Daily persuasion experienced | 0.85* | 0.71 | 0.99 | 1.000 | 9896.79 | 7775.98 | 0.980 | 0.249 | Moderate Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.03 | 0.84 | 1.24 | 1.000 | 9229.64 | 7954.31 | 0.607 | 0.041 | Strong Evidence for Null |
| Daily pressure experienced | 1.84* | 1.18 | 2.68 | 1.001 | 5608.70 | 6574.26 | 0.994 | 3.418 | Moderate Evidence |
| Daily pressure utilized (partner’s view) | 1.22 | 0.71 | 2.06 | 1.001 | 7420.47 | 6712.38 | 0.808 | 0.153 | Moderate Evidence for Null |
| Daily pushing experienced | 1.17 | 0.97 | 1.43 | 1.001 | 7757.54 | 7485.59 | 0.946 | 0.151 | Moderate Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.91 | 0.71 | 1.17 | 1.000 | 9792.98 | 8248.45 | 0.770 | 0.064 | Strong Evidence for Null |
| Day | 1.47 | 0.75 | 2.89 | 1.000 | 13856.59 | 9556.08 | 0.871 | 0.255 | Moderate Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.12 | 0.40 | 3.11 | 1.000 | 4004.78 | 6205.61 | 0.586 | 0.209 | Moderate Evidence for Null |
| Mean persuasion utilized (partner’s view) | 1.38 | 0.45 | 4.31 | 1.000 | 4278.63 | 6604.64 | 0.711 | 0.252 | Moderate Evidence for Null |
| Mean pressure experienced | 3.51* | 1.18 | 10.71 | 1.000 | 4792.44 | 6629.78 | 0.990 | 3.171 | Moderate Evidence |
| Mean pressure utilized (partner’s view) | 1.17 | 0.37 | 3.66 | 1.000 | 4762.77 | 6973.89 | 0.612 | 0.233 | Moderate Evidence for Null |
| Mean pushing experienced | 1.23 | 0.28 | 5.62 | 1.000 | 5266.91 | 7722.24 | 0.605 | 0.312 | Weak Evidence for Null |
| Mean pushing utilized (partner’s view) | 0.11* | 0.02 | 0.64 | 1.000 | 7169.66 | 7894.75 | 0.992 | 7.489 | Moderate Evidence |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 0.82 | 0.47 | 1.25 | 1.00 | 4256.66 | 7026.55 | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.18 | 0.01 | 0.43 | 1.00 | 1818.16 | 4469.30 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.22 | 0.01 | 0.51 | 1.00 | 3273.96 | 4646.21 | NA | NA | NA |
| sd(Daily pressure experienced) | 0.56 | 0.09 | 1.14 | 1.00 | 2689.26 | 2386.75 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.50 | 0.02 | 1.55 | 1.00 | 2929.20 | 4951.16 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.22 | 0.01 | 0.50 | 1.00 | 3370.38 | 4130.06 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.18 | 0.01 | 0.57 | 1.00 | 4830.97 | 5284.06 | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| disc | 1.00 | 1.00 | 1.00 | NA | NA | NA | NA | NA | NA |
mcmc_plot(reactance_ordinal,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(reactance_ordinal),
priors = TRUE
) +
coord_cartesian(xlim = c(-6, 6)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
## Possible multicollinearity between b_Intercept[4] and b_Intercept[2] (r
## = 0.76), b_Intercept[4] and b_Intercept[3] (r = 0.83),
## b_pressure_self_cb and b_persuasion_self_cb (r = 0.72),
## b_pressure_partner_cb and b_persuasion_partner_cb (r = 0.79). This might
## lead to inappropriate results. See 'Details' in '?rope'.
conditional_spaghetti(
reactance_ordinal,
effects = c('persuasion_self_cw', 'pressure_self_cw')
, group_var = 'coupleID'
#, n_groups = 15
, plot_full_range = T
)\(persuasion_self_cw
<img
src="01_FinalModels_files/figure-html/report_reactance_ordinal-4.png"
width="2400" />\)pressure_self_cw
##
## Group Estimate 2.5 % 97.5 %
## 0 0.68180 0.65445 0.7078
## 1 0.09430 0.07497 0.1157
## 2 0.08365 0.06601 0.1047
## 3 0.06983 0.05482 0.0875
## 4 0.06396 0.05134 0.0776
## 5 0.00531 0.00172 0.0116
##
## Type: response
## Columns: group, estimate, conf.low, conf.high
introduce_binary_reactance <- function(data) {
data$is_reactance <- factor(data$reactance > 0, levels = c(FALSE, TRUE), labels = c(0, 1))
return(data)
}
df_double <- introduce_binary_reactance(df_double)
if (use_mi) {
for (i in seq_along(implist)) {
implist[[i]] <- introduce_binary_reactance(implist[[i]])
}
}
formula <- bf(
is_reactance ~
persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw +
persuasion_self_cb + persuasion_partner_cb +
pressure_self_cb + pressure_partner_cb +
pushing_self_cb + pushing_partner_cb +
day +
# Random effects
(persuasion_self_cw + persuasion_partner_cw +
pressure_self_cw + pressure_partner_cw +
pushing_self_cw + pushing_partner_cw | coupleID)
#, autocor = autocor_str
)
prior1 <- c(
brms::set_prior("normal(0, 2.5)", class = "b")
, brms::set_prior("normal(0, 10)", class = "Intercept", lb=0, ub=5) # range of the outcome scale
, brms::set_prior("normal(0, 2)", class = "sd", group = "coupleID", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sigma", lb = 0)
#, brms::set_prior("cauchy(0, 2)", class = "sderr", lb = 0)
#, autocor_prior
)
#brms::validate_prior(
# prior1,
# formula = formula,
# data = df_double,
# family = bernoulli()
# )
#df_minimal <- df_double[, c("AorB", all.vars(as.formula(formula)))]
is_reactance <- my_brm(
mi = use_mi,
imputed_data = implist,
formula = formula,
prior = prior1,
data = df_double,
family = brms::bernoulli(),
#control = list(adapt_delta = 0.95, max_treedepth = 15),
iter = iterations,
warmup = warmup,
chains = 4,
cores = 4,
seed = 7777,
file = file.path("models_cache_brms", paste0("is_reactance_NOARNOAR_", suffix))
#, file_refit = 'always'
)## Warning: Rows containing NAs were excluded from the model.
##
## Divergences:
## 0 of 12000 iterations ended with a divergence.
##
## Tree depth:
## 0 of 12000 iterations saturated the maximum tree depth of 10.
##
## Energy:
## E-BFMI indicated no pathological behavior.
## Using 10 posterior draws for ppc type 'ecdf_overlay' by default.
## Using 10 posterior draws for ppc type 'dens_overlay' by default.
## Warning: Found 55 observations with a pareto_k > 0.7 in model 'model'. We
## recommend to set 'moment_match = TRUE' in order to perform moment matching for
## problematic observations.
##
## Computed from 12000 by 756 log-likelihood matrix.
##
## Estimate SE
## elpd_loo -363.1 16.0
## p_loo 80.1 6.0
## looic 726.3 32.0
## ------
## MCSE of elpd_loo is NA.
## MCSE and ESS estimates assume MCMC draws (r_eff in [0.4, 1.5]).
##
## Pareto k diagnostic values:
## Count Pct. Min. ESS
## (-Inf, 0.7] (good) 701 92.7% 429
## (0.7, 1] (bad) 49 6.5% <NA>
## (1, Inf) (very bad) 6 0.8% <NA>
## See help('pareto-k-diagnostic') for details.
##
## DHARMa outlier test based on exact binomial test with approximate
## expectations
##
## data: model.check
## outliers at both margin(s) = 1, observations = 756, p-value = 1
## alternative hypothesis: true probability of success is not equal to 0.001998002
## 95 percent confidence interval:
## 0.0000334886 0.0073476538
## sample estimates:
## frequency of outliers (expected: 0.001998001998002 )
## 0.001322751
summarize_brms(
is_reactance,
model_rows_fixed = model_rows_fixed,
model_rows_random = model_rows_random,
model_rownames_fixed = model_rownames_fixed,
model_rownames_random = model_rownames_random,
exponentiate = T) %>%
print_df(rows_to_pack = rows_to_pack)## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
| OR | l-95% CI | u-95% CI | Rhat | Bulk_ESS | Tail_ESS | p_dir | BF | BF_Evidence | |
|---|---|---|---|---|---|---|---|---|---|
| Intercept | 0.29* | 0.16 | 0.50 | 1.000 | 13412.80 | 10197.69 | 1.000 | >100 | Overwhelming Evidence |
| Within-Person Effects | |||||||||
| Daily persuasion experienced | 0.84 | 0.69 | 1.01 | 1.001 | 12653.33 | 8961.78 | 0.966 | 0.197 | Moderate Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.13 | 0.85 | 1.54 | 1.000 | 9878.26 | 8807.43 | 0.789 | 0.076 | Strong Evidence for Null |
| Daily pressure experienced | 2.04* | 1.03 | 4.57 | 1.000 | 8289.60 | 6530.31 | 0.979 | 1.397 | Weak Evidence |
| Daily pressure utilized (partner’s view) | 1.44 | 0.58 | 4.04 | 1.000 | 8810.48 | 6987.21 | 0.799 | 0.241 | Moderate Evidence for Null |
| Daily pushing experienced | 1.28* | 1.01 | 1.64 | 1.001 | 12865.46 | 8547.86 | 0.979 | 0.398 | Weak Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.89 | 0.60 | 1.31 | 1.000 | 14162.09 | 8870.67 | 0.735 | 0.095 | Strong Evidence for Null |
| Day | 1.64 | 0.77 | 3.51 | 1.000 | 19648.18 | 9310.83 | 0.900 | 0.359 | Weak Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Between-Person Effects | |||||||||
| Mean persuasion experienced | 1.99 | 0.60 | 6.80 | 1.000 | 6422.05 | 7842.49 | 0.870 | 0.443 | Weak Evidence for Null |
| Mean persuasion utilized (partner’s view) | 1.90 | 0.52 | 7.15 | 1.000 | 6799.76 | 8735.29 | 0.829 | 0.409 | Weak Evidence for Null |
| Mean pressure experienced | 17.91* | 2.33 | 159.59 | 1.000 | 8975.03 | 8541.37 | 0.997 | 20.141 | Strong Evidence |
| Mean pressure utilized (partner’s view) | 2.27 | 0.24 | 19.14 | 1.000 | 8119.78 | 8948.63 | 0.769 | 0.607 | Weak Evidence for Null |
| Mean pushing experienced | 0.83 | 0.12 | 6.30 | 1.000 | 8730.85 | 8605.26 | 0.580 | 0.408 | Weak Evidence for Null |
| Mean pushing utilized (partner’s view) | 0.08* | 0.01 | 0.66 | 1.000 | 10022.27 | 10004.57 | 0.990 | 7.272 | Moderate Evidence |
| Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||
| sd(Intercept) | 1.18 | 0.75 | 1.74 | 1.00 | 5382.54 | 7890.40 | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.21 | 0.01 | 0.51 | 1.00 | 2939.60 | 5289.74 | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.50 | 0.12 | 0.97 | 1.00 | 4502.23 | 4854.72 | NA | NA | NA |
| sd(Daily pressure experienced) | 1.12 | 0.16 | 2.43 | 1.00 | 2982.38 | 3385.24 | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.97 | 0.04 | 2.73 | 1.00 | 4249.53 | 5650.95 | NA | NA | NA |
| sd(Daily pushing experienced) | 0.25 | 0.01 | 0.60 | 1.00 | 4754.94 | 5282.30 | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.31 | 0.01 | 0.95 | 1.00 | 4810.38 | 6592.98 | NA | NA | NA |
| Additional Parameters | |||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | NA | NA | NA | NA | NA | NA | NA | NA | NA |
mcmc_plot(is_reactance,
variable = c(
'b_persuasion_self_cw',
'b_persuasion_partner_cw',
'b_pressure_self_cw',
'b_pressure_partner_cw',
'b_pushing_self_cw',
'b_pushing_partner_cw'
),
#regex = TRUE,
type = 'areas',
prob = 0.95)plot(
bayestestR::p_direction(is_reactance),
priors = TRUE
) +
coord_cartesian(xlim = c(-6, 6)) +
theme_bw()## Warning in `==.default`(dens$Parameter, parameter): longer object length is not
## a multiple of shorter object length
## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length
conditional_spaghetti(
is_reactance,
effects = c('pressure_self_cw', 'pushing_self_cw'),
group_var = 'coupleID',
plot_full_range = TRUE
)\(pressure_self_cw
<img
src="01_FinalModels_files/figure-html/report_is_reactance-4.png"
width="2400" />\)pushing_self_cw
##
## Estimate 2.5 % 97.5 %
## 0.328 0.303 0.355
##
## Type: response
## Columns: estimate, conf.low, conf.high
## Hypothesis Tests for class b:
## Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio
## 1 (pressure_self_cw... > 0 0.47 0.39 -0.15 1.13 8.86
## Post.Prob Star
## 1 0.9
## ---
## 'CI': 90%-CI for one-sided and 95%-CI for two-sided hypotheses.
## '*': For one-sided hypotheses, the posterior probability exceeds 95%;
## for two-sided hypotheses, the value tested against lies outside the 95%-CI.
## Posterior probabilities of point hypotheses assume equal prior probabilities.
if (report_ordinal) {
model_rows_random_final <- model_rows_random_ordinal
model_rows_fixed_final <- model_rows_fixed_ordinal
model_rownames_fixed_final <- model_rownames_fixed_ordinal
model_rownames_random_final <- model_rownames_random_ordinal
rows_to_pack_final <- rows_to_pack_ordinal
} else {
model_rows_random_final <- model_rows_random_hu
model_rows_fixed_final <- model_rows_fixed_hu
model_rownames_fixed_final <- model_rownames_fixed_hu
model_rownames_random_final <- model_rownames_random_hu
rows_to_pack_final <- rows_to_pack_hu
}
bayesfactor = TRUE
all_models <- report_side_by_side(
pa_sub,
pa_obj_log,
mood_gauss,
reactance_ordinal,
is_reactance,
bayesfactor = bayesfactor,
model_rows_random = model_rows_random_final,
model_rows_fixed = model_rows_fixed_final,
model_rownames_random = model_rownames_random_final,
model_rownames_fixed = model_rownames_fixed_final
) [1] “pa_sub”
## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
## Warning in summarize_brms(model, short_version = TRUE, bayesfactor =
## bayesfactor, : Coefficients were exponentiated. Double check if this was
## intended.
[1] “pa_obj_log”
## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
## Warning: Coefficients were exponentiated. Double check if this was intended.
[1] “mood_gauss”
## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
[1] “reactance_ordinal”
## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
[1] “is_reactance”
## Sampling priors, please wait...
## Warning: Bayes factors might not be precise.
## For precise Bayes factors, sampling at least 40,000 posterior samples is
## recommended.
# pretty printing
if (bayesfactor) {
summary_all_models <- all_models %>%
print_df(rows_to_pack = rows_to_pack_final) %>%
add_header_above(
c(" ", "Subjective MVPA Hurdle Lognormal" = 5,
"Device-Based MVPA Log (Gaussian)" = 5,
"Mood Gaussian" = 5,
"Reactance Ordinal" = 5,
"Reactance Dichotome" = 5)
)
export_xlsx(
summary_all_models,
rows_to_pack = rows_to_pack_final,
file.path("Output", "AllModels_experimental_noAR.xlsx"),
merge_option = 'both',
simplify_2nd_row = TRUE,
colwidths = c(38,
7.2,13.3,7.2,7.2,24,
7.2,13.3,7.2,7.2,24,
7.2,13.3,7.2,7.2,24,
7.2,13.3,7.2,7.2,24,
7.2,13.3,7.2,7.2,24),
line_above_rows = c(1,2),
line_below_rows = c(-1)
)
} else {
summary_all_models <- all_models %>%
print_df(rows_to_pack = rows_to_pack_final) %>%
add_header_above(
c(" ", "Subjective MVPA Hurdle Lognormal" = 3,
"Device-Based MVPA Log (Gaussian)" = 3,
"Mood Gaussian" = 3,
"Reactance Ordinal" = 3,
"Reactance Dichotome" = 3)
)
export_xlsx(
summary_all_models,
rows_to_pack = rows_to_pack_final,
file.path("Output", "AllModels_experimental_noAR.xlsx"),
merge_option = 'both',
simplify_2nd_row = TRUE,
colwidths = c(38,
7.2,13.3,7.2,
7.2,13.3,7.2,
7.2,13.3,7.2,
7.2,13.3,7.2,
7.2,13.3,7.2),
line_above_rows = c(1,2),
line_below_rows = c(-1)
)
}##
## Attaching package: 'rvest'
## The following object is masked from 'package:readr':
##
## guess_encoding
| exp(Est.) pa_sub | 95% CI pa_sub | p_dir pa_sub | BF pa_sub | BF_Evidence pa_sub | exp(Est.) pa_obj_log | 95% CI pa_obj_log | p_dir pa_obj_log | BF pa_obj_log | BF_Evidence pa_obj_log | b mood_gauss | 95% CI mood_gauss | p_dir mood_gauss | BF mood_gauss | BF_Evidence mood_gauss | OR reactance_ordinal | 95% CI reactance_ordinal | p_dir reactance_ordinal | BF reactance_ordinal | BF_Evidence reactance_ordinal | OR is_reactance | 95% CI is_reactance | p_dir is_reactance | BF is_reactance | BF_Evidence is_reactance | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Intercept | 47.90* | [42.22, 54.30] | 1.000 | >100 | Overwhelming Evidence | 117.41* | [105.48, 130.41] | 1.000 | >100 | Overwhelming Evidence | 3.70* | [ 3.48, 3.91] | 1.000 | >100 | Overwhelming Evidence | NA | NA | NA | NA | NA | 0.29* | [0.16, 0.50] | 1.000 | >100 | Overwhelming Evidence |
| Hurdle Intercept | 1.21 | [ 0.87, 1.69] | 0.868 | 0.012 | Very Strong Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Within-Person Effects | |||||||||||||||||||||||||
| Daily persuasion experienced | 1.03 | [ 0.97, 1.08] | 0.828 | 0.028 | Very Strong Evidence for Null | 1.03 | [ 1.00, 1.06] | 0.966 | 0.036 | Strong Evidence for Null | 0.00 | [-0.04, 0.05] | 0.553 | 0.004 | Very Strong Evidence for Null | 0.85* | [0.71, 0.99] | 0.980 | 0.253 | Moderate Evidence for Null | 0.84 | [0.69, 1.01] | 0.966 | 0.199 | Moderate Evidence for Null |
| Daily persuasion utilized (partner’s view) | 1.03 | [ 0.98, 1.08] | 0.899 | 0.035 | Strong Evidence for Null | 1.02 | [ 0.99, 1.05] | 0.888 | 0.013 | Very Strong Evidence for Null | 0.02 | [-0.02, 0.07] | 0.829 | 0.007 | Very Strong Evidence for Null | 1.03 | [0.84, 1.24] | 0.607 | 0.041 | Strong Evidence for Null | 1.13 | [0.85, 1.54] | 0.789 | 0.077 | Strong Evidence for Null |
| Daily pressure experienced | 0.89* | [ 0.80, 0.99] | 0.984 | 0.484 | Weak Evidence for Null | 0.94 | [ 0.88, 1.01] | 0.960 | 0.072 | Strong Evidence for Null | -0.04 | [-0.14, 0.07] | 0.767 | 0.014 | Very Strong Evidence for Null | 1.84* | [1.18, 2.68] | 0.994 | 3.366 | Moderate Evidence | 2.04* | [1.03, 4.57] | 0.979 | 1.451 | Weak Evidence |
| Daily pressure utilized (partner’s view) | 0.94 | [ 0.86, 1.03] | 0.915 | 0.072 | Strong Evidence for Null | 0.98 | [ 0.92, 1.05] | 0.714 | 0.015 | Very Strong Evidence for Null | -0.02 | [-0.14, 0.08] | 0.661 | 0.011 | Very Strong Evidence for Null | 1.22 | [0.71, 2.06] | 0.808 | 0.149 | Moderate Evidence for Null | 1.44 | [0.58, 4.04] | 0.799 | 0.251 | Moderate Evidence for Null |
| Daily pushing experienced | 1.03 | [ 0.96, 1.10] | 0.775 | 0.032 | Strong Evidence for Null | 1.03 | [ 0.98, 1.08] | 0.900 | 0.025 | Very Strong Evidence for Null | 0.02 | [-0.04, 0.09] | 0.768 | 0.008 | Very Strong Evidence for Null | 1.17 | [0.97, 1.43] | 0.946 | 0.145 | Moderate Evidence for Null | 1.28* | [1.01, 1.64] | 0.979 | 0.395 | Weak Evidence for Null |
| Daily pushing utilized (partner’s view) | 0.99 | [ 0.93, 1.05] | 0.618 | 0.021 | Very Strong Evidence for Null | 1.02 | [ 0.97, 1.06] | 0.771 | 0.011 | Very Strong Evidence for Null | 0.08* | [ 0.01, 0.14] | 0.984 | 0.079 | Strong Evidence for Null | 0.91 | [0.71, 1.17] | 0.770 | 0.064 | Strong Evidence for Null | 0.89 | [0.60, 1.31] | 0.735 | 0.096 | Strong Evidence for Null |
| Day | 1.01 | [ 0.89, 1.13] | 0.551 | 0.042 | Strong Evidence for Null | 0.97 | [ 0.91, 1.04] | 0.785 | 0.020 | Very Strong Evidence for Null | 0.26* | [ 0.15, 0.37] | 1.000 | 50.164 | Very Strong Evidence | 1.47 | [0.75, 2.89] | 0.871 | 0.256 | Moderate Evidence for Null | 1.64 | [0.77, 3.51] | 0.900 | 0.364 | Weak Evidence for Null |
| Daily weartime | NA | NA | NA | NA | NA | 1.00* | [ 1.00, 1.00] | 1.000 | 0.070 | Strong Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Conditional Between-Person Effects | |||||||||||||||||||||||||
| Mean persuasion experienced | 1.01 | [ 0.74, 1.38] | 0.533 | 0.102 | Moderate Evidence for Null | 1.10 | [ 0.82, 1.46] | 0.748 | 0.075 | Strong Evidence for Null | 0.33 | [-0.21, 0.90] | 0.889 | 0.118 | Moderate Evidence for Null | 1.12 | [0.40, 3.11] | 0.586 | 0.204 | Moderate Evidence for Null | 1.99 | [0.60, 6.80] | 0.870 | 0.454 | Weak Evidence for Null |
| Mean persuasion utilized (partner’s view) | 0.98 | [ 0.72, 1.33] | 0.543 | 0.106 | Moderate Evidence for Null | 0.98 | [ 0.73, 1.30] | 0.559 | 0.060 | Strong Evidence for Null | 0.22 | [-0.32, 0.79] | 0.790 | 0.076 | Strong Evidence for Null | 1.38 | [0.45, 4.31] | 0.711 | 0.262 | Moderate Evidence for Null | 1.90 | [0.52, 7.15] | 0.829 | 0.417 | Weak Evidence for Null |
| Mean pressure experienced | 1.15 | [ 0.80, 1.65] | 0.772 | 0.158 | Moderate Evidence for Null | 0.98 | [ 0.73, 1.31] | 0.560 | 0.062 | Strong Evidence for Null | -0.31 | [-0.86, 0.23] | 0.874 | 0.101 | Moderate Evidence for Null | 3.51* | [1.18, 10.71] | 0.990 | 3.142 | Moderate Evidence | 17.91* | [2.33, 159.59] | 0.997 | 20.152 | Strong Evidence |
| Mean pressure utilized (partner’s view) | 0.89 | [ 0.62, 1.29] | 0.744 | 0.155 | Moderate Evidence for Null | 0.97 | [ 0.73, 1.28] | 0.594 | 0.060 | Strong Evidence for Null | -0.30 | [-0.84, 0.24] | 0.871 | 0.099 | Strong Evidence for Null | 1.17 | [0.37, 3.66] | 0.612 | 0.239 | Moderate Evidence for Null | 2.27 | [0.24, 19.14] | 0.769 | 0.597 | Weak Evidence for Null |
| Mean pushing experienced | 1.32 | [ 0.84, 2.07] | 0.891 | 0.322 | Weak Evidence for Null | 0.97 | [ 0.65, 1.45] | 0.553 | 0.080 | Strong Evidence for Null | 0.22 | [-0.54, 0.99] | 0.714 | 0.091 | Strong Evidence for Null | 1.23 | [0.28, 5.62] | 0.605 | 0.308 | Weak Evidence for Null | 0.83 | [0.12, 6.30] | 0.580 | 0.405 | Weak Evidence for Null |
| Mean pushing utilized (partner’s view) | 1.40 | [ 0.88, 2.21] | 0.925 | 0.454 | Weak Evidence for Null | 1.25 | [ 0.83, 1.85] | 0.859 | 0.152 | Moderate Evidence for Null | 0.35 | [-0.39, 1.12] | 0.825 | 0.121 | Moderate Evidence for Null | 0.11* | [0.02, 0.64] | 0.992 | 7.898 | Moderate Evidence | 0.08* | [0.01, 0.66] | 0.990 | 7.042 | Moderate Evidence |
| Mean weartime | NA | NA | NA | NA | NA | 1.00 | [ 1.00, 1.00] | 0.909 | 0.000 | Very Strong Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Within-Person Effects | |||||||||||||||||||||||||
| Hu Daily persuasion experienced | 0.65* | [ 0.57, 0.73] | 1.000 | >100 | Overwhelming Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily persuasion utilized (partner’s view) | 0.75* | [ 0.67, 0.84] | 1.000 | >100 | Overwhelming Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure experienced | 1.23 | [ 0.88, 1.71] | 0.898 | 0.152 | Moderate Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pressure utilized (partner’s view) | 0.66* | [ 0.42, 0.95] | 0.988 | 0.890 | Weak Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing experienced | 0.58* | [ 0.40, 0.78] | 1.000 | 25.195 | Strong Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily pushing utilized (partner’s view) | 0.54* | [ 0.41, 0.69] | 1.000 | >100 | Overwhelming Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Day | 1.09 | [ 0.85, 1.42] | 0.750 | 0.067 | Strong Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Daily weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hurdle Between-Person Effects | |||||||||||||||||||||||||
| Hu Mean persuasion experienced | 0.83 | [ 0.36, 1.87] | 0.680 | 0.183 | Moderate Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean persuasion utilized (partner’s view) | 0.83 | [ 0.36, 1.89] | 0.671 | 0.173 | Moderate Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure experienced | 3.31* | [ 1.36, 8.35] | 0.995 | 6.142 | Moderate Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pressure utilized (partner’s view) | 1.79 | [ 0.74, 4.48] | 0.905 | 0.428 | Weak Evidence for Null | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing experienced | 0.35 | [ 0.11, 1.11] | 0.962 | 1.141 | Weak Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean pushing utilized (partner’s view) | 0.34 | [ 0.11, 1.10] | 0.964 | 1.261 | Weak Evidence | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Hu Mean weartime | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Random Effects | |||||||||||||||||||||||||
| sd(Intercept) | 0.32 | [0.24, 0.42] | NA | NA | NA | 0.31 | [0.24, 0.40] | NA | NA | NA | 0.60 | [0.47, 0.78] | NA | NA | NA | 0.82 | [0.47, 1.25] | NA | NA | NA | 1.18 | [0.75, 1.74] | NA | NA | NA |
| sd(Hurdle Intercept) | 0.90 | [0.69, 1.17] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Daily persuasion experienced) | 0.12 | [0.08, 0.17] | NA | NA | NA | 0.05 | [0.02, 0.08] | NA | NA | NA | 0.04 | [0.00, 0.10] | NA | NA | NA | 0.18 | [0.01, 0.43] | NA | NA | NA | 0.21 | [0.01, 0.51] | NA | NA | NA |
| sd(Daily persuasion utilized (partner’s view)) | 0.09 | [0.05, 0.13] | NA | NA | NA | 0.06 | [0.03, 0.09] | NA | NA | NA | 0.08 | [0.01, 0.13] | NA | NA | NA | 0.22 | [0.01, 0.51] | NA | NA | NA | 0.50 | [0.12, 0.97] | NA | NA | NA |
| sd(Daily pressure experienced) | 0.08 | [0.00, 0.24] | NA | NA | NA | 0.05 | [0.00, 0.14] | NA | NA | NA | 0.08 | [0.00, 0.24] | NA | NA | NA | 0.56 | [0.09, 1.14] | NA | NA | NA | 1.12 | [0.16, 2.43] | NA | NA | NA |
| sd(Daily pressure utilized (partner’s view)) | 0.07 | [0.00, 0.19] | NA | NA | NA | 0.04 | [0.00, 0.12] | NA | NA | NA | 0.09 | [0.00, 0.26] | NA | NA | NA | 0.50 | [0.02, 1.55] | NA | NA | NA | 0.97 | [0.04, 2.73] | NA | NA | NA |
| sd(Daily pushing experienced) | 0.11 | [0.04, 0.19] | NA | NA | NA | 0.07 | [0.01, 0.15] | NA | NA | NA | 0.06 | [0.00, 0.14] | NA | NA | NA | 0.22 | [0.01, 0.50] | NA | NA | NA | 0.25 | [0.01, 0.60] | NA | NA | NA |
| sd(Daily pushing utilized (partner’s view)) | 0.09 | [0.02, 0.17] | NA | NA | NA | 0.04 | [0.00, 0.10] | NA | NA | NA | 0.07 | [0.00, 0.17] | NA | NA | NA | 0.18 | [0.01, 0.57] | NA | NA | NA | 0.31 | [0.01, 0.95] | NA | NA | NA |
| sd(Hu Daily persuasion experienced) | 0.18 | [0.02, 0.34] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily persuasion utilized (partner’s view)) | 0.17 | [0.03, 0.33] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure experienced) | 0.31 | [0.01, 0.89] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pressure utilized (partner’s view)) | 0.34 | [0.01, 0.99] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing experienced) | 0.64 | [0.32, 1.07] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sd(Hu Daily pushing utilized (partner’s view)) | 0.32 | [0.05, 0.64] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| Additional Parameters | |||||||||||||||||||||||||
| ar[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| ma[1] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| cosy | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| nu | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| shape | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sderr | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| sigma | 0.68 | [0.66, 0.71] | NA | NA | NA | 0.57 | [0.56, 0.59] | NA | NA | NA | 0.96 | [0.94, 0.98] | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
Analyses were conducted using the R Statistical language (version 4.4.1; R Core Team, 2024) on Windows 11 x64 (build 22635)